The Mid-Level I&C Reliability Analyst plays a key role in the deployment, monitoring, and optimization of predictive maintenance strategies for instrumentation and control systems. The role involves analyzing condition monitoring data, identifying early failure indicators, and driving improvements to asset reliability through technical assessments and maintenance strategy development.
Predictive Maintenance Implementation:
Deploy and maintain predictive maintenance systems (vibration monitoring, temperature sensors, valve diagnostics, etc.) for I&C assets.
Condition Monitoring Analysis:
Analyze real-time and historical condition data from sensors and control systems to detect trends, abnormalities, and degradation.
Performance Diagnostics:
Assess the health of instrumentation devices and control loops, identifying issues like sensor drift, signal loss, or valve sticking.
Root Cause Analysis (RCA):
Conduct or assist in structured failure investigations to identify root causes and recommend preventive or corrective actions.
Reliability Reporting:
Generate periodic reliability and asset health reports, including KPIs such as MTBF, MTTR, and availability.
Maintenance Strategy Support:
Contribute to the development and optimization of preventive and predictive maintenance strategies, including RCM and FMEA activities.
Tool and System Management:
Manage condition monitoring tools (e.g., Emerson AMS, Honeywell Field Device Manager, PI System) and assist in CMMS integration.
Collaboration with Field Teams:
Work closely with field instrumentation teams, automation engineers, and maintenance planners to align reliability insights with execution.
Continuous Improvement:
Recommend enhancements to sensing systems, data accuracy, calibration schedules, and diagnostic practices to improve asset reliability.
Instrumentation Health Monitoring:
Monitor performance of sensors, transmitters, analyzers, and control valves to detect early signs of failure.
Data Interpretation and Diagnostics:
Use software tools and analytics to assess trends in sensor readings and identify abnormal behavior or potential failures.
Failure Pattern Recognition:
Identify recurring issues and systemic weaknesses using structured data and field feedback.
Asset Criticality and Reliability Metrics:
Support ranking of assets based on criticality and reliability performance to prioritize maintenance resources.
Digital Reliability Tools:
Operate predictive maintenance platforms and reliability databases; support digital transformation efforts in asset management.
Bachelor’s Degree or Diploma in Instrumentation, Electrical, Electronics, or Mechatronics Engineering.
2–5 years of relevant experience in I&C maintenance, reliability engineering, or condition-based monitoring.
Familiarity with predictive maintenance technologies (e.g., vibration, thermography, acoustic monitoring).
Experience with reliability tools such as CMMS, RCM software, and asset health monitoring platforms.
Working knowledge of industrial automation (PLC, SCADA, DCS) and field instrumentation.
Strong analytical, reporting, and problem-solving skills.
Understanding of safety, environmental, and regulatory compliance in industrial settings.